Algorithm for Predicting Compound Protein Interaction Using Tanimoto Similarity and Klekota-roth Fingerprint

Isnan Mulia, Wisnu Ananta Kusuma, Farit Mochamad Afendi

Abstract


This research aimed to develop a method for predicting interaction between chemical compounds contained in herbs and proteins related to particular disease. The algorithm of this method is based on binary local models algorithm, with protein similarity section is omitted. Klekota-Roth fingerprint is used for the compound's representation. In the development process of the method, three similarity functions are compared: Tanimoto, Cosine, and Dice. Youden’s index is used to evaluate optimum threshold value. The result showed that Tanimoto similarity function yielded higher similarity values and higher AUC value than those of the other two functions. Moreover, the optimum threshold value obtained is 0.65. Therefore, Tanimoto similarity function and threshold value 0.65 are selected to be used on the prediction method. The average evaluation accuracy of the developed algorithm is only about 50%. The low accuracy value is allegedly caused by the only use of compound similarity on the prediction method, without including the protein similarity.


Keywords


tanimoto similarity; jamu; klekota-roth fingerprint; network pharmacology

Full Text:

PDF


DOI: http://dx.doi.org/10.12928/telkomnika.v16i4.5916

Article Metrics

Abstract view : 314 times
PDF - 99 times

Refbacks

  • There are currently no refbacks.


Copyright (c) 2019 Universitas Ahmad Dahlan

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

TELKOMNIKA Telecommunication, Computing, Electronics and Control
ISSN: 1693-6930, e-ISSN: 2302-9293
Universitas Ahmad Dahlan, 4th Campus, 9th Floor, LPPI Room
Jl. Ringroad Selatan, Kragilan, Tamanan, Banguntapan, Bantul, Yogyakarta, Indonesia 55191
Phone: +62 (274) 563515, 511830, 379418, 371120 ext. 4902, Fax: +62 274 564604

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

View TELKOMNIKA Stats